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International Journal of Digital Multimedia Broadcasting
Volume 2010 (2010), Article ID 424036, 20 pages
Research Article

Collaborative Spectrum Sensing Optimisation Algorithms for Cognitive Radio Networks

Centre for Communication Systems Research, University of Surrey, Guildford GU2 7XH, UK

Received 28 October 2009; Accepted 17 March 2010

Academic Editor: Massimiliano Laddomada

Copyright © 2010 Kamran Arshad et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The main challenge for a cognitive radio is to detect the existence of primary users reliably in order to minimise the interference to licensed communications. Hence, spectrum sensing is a most important requirement of a cognitive radio. However, due to the channel uncertainties, local observations are not reliable and collaboration among users is required. Selection of fusion rule at a common receiver has a direct impact on the overall spectrum sensing performance. In this paper, optimisation of collaborative spectrum sensing in terms of optimum decision fusion is studied for hard and soft decision combining. It is concluded that for optimum fusion, the fusion centre must incorporate signal-to-noise ratio values of cognitive users and the channel conditions. A genetic algorithm-based weighted optimisation strategy is presented for the case of soft decision combining. Numerical results show that the proposed optimised collaborative spectrum sensing schemes give better spectrum sensing performance.